New approach for a unified formalism for spectral and thermodynamic properties of interacting-electron systems 

Addressing increased need for more accurate predictions of materials spectra and thermodynamics, NCCR MARVEL researchers Tommaso Chiarotti and Nicola Marzari, and colleague Andrea Ferretti, introduce a treatment of frequency dependence allowing for the algorithmic inversion method on sum over poles (AIM-SOP) for solving Dyson-like equations and handling frequency-dependent quantities in dynamical theories. Specializing to the case of many-body perturbation theory applied to the homogeneous electron gas, they show that the AIM-SOP approach provides a unified formalism for generating the spectral and thermodynamic properties of an interacting-electron system. The authors are now working on generalizing the AIM-SOP method to non-homogeneous crystalline systems.  

Newly released AiiDA v2.0 improves on performance and usability while maintaining a stable API

The developers of AiiDA have released AiiDA v2.0. The culmination of more than two years of work, the update focused on re-designing the codebase to make it more performant, user-friendly and maintainable, with minimal changes to the API.

Psi-k conference

Psi-k 2022 is the 6th general conference for the worldwide Psi-k community. Typically held every 5 years, this event is the largest worldwide in first-principles simulations. With more than 1000 participants attending the past 2010 and 2015 editions, it promises to be the most exciting, defining event in the field, offering an intense but enjoyable atmosphere, in addition to a chance to explore the beautiful region around Lausanne and Lake Geneva.  

MARVEL Distinguished Lecture — Alán Aspuru-Guzik

The 31st NCCR MARVEL Distinguished Lecture will be given by Prof. Alán Aspuru-Guzik, professor of chemistry and computer science at the University of Toronto, and entitled: "There is no time for science as usual: Materials Acceleration Platforms".

First-Principles Modelling of Defects in Solids - Workshop

The workshop will take place June 13-15, 2022 at ETH in Zurich. Apart from scientific concerns, the event aims to address environmental issues as well, and the utmost will be done to mitigate the impact of the workshop on the environment.

Swiss Equivariant Machine Learning Workshop

Machine learning (ML) based atomistic models are often faced with the challenge of learning physical or chemical properties that have well-defined transformations (equivariance) under translation, rotation,  and reflections of the corresponding atomic structures. The last few years have seen significant progress on enhancing ML approaches by including symmetry preserving operations, which has led to noteworthy improvements in both the accuracy and data-efficiency of models predicting physical quantities.